Accepting government-issued identification (ID) cards for identity validation is becoming more prevalent as data transfer speeds improve and as mobile cameras become more widely used. A typical modern smartphone, for example, can be utilized to take a clear picture of an ID card with sufficient resolution and clarity for verification of printed security indicia, facial recognition, etc. However, the captured digital image can result in a large file, often ranging in size from 2.5 MB to 10 MB. When such an ID image is uploaded to a verification server, the upload process may be relatively quick (for example, several seconds assuming an upload speed of ˜20 Mbps), but the time required by the server's verification software to scan, process, and analyze the millions of pixels to extract important data for verification or rejection can take an additional five to forty seconds. Such a process can be very server intensive and can require huge amount of server CPU and memory.
Certain businesses rely upon digital ID image validation before providing goods and/or services to customers, and it can be detrimental to both the business and customer if it is determined, after taking a digital photo of the ID card and uploading the ID image to a verification server, that the image is unusable (e.g., too blurry, was taken from too far or too close, the subject ID card does not qualify for such a verification process, etc.). ID card validation that utilizes a camera on a user's mobile computing device can be particularly challenging due to various factors such as poor lighting, blurring, incorrect framing, etc.
Accordingly, there is a need for improved systems and methods to address such challenges. Embodiments of the present disclosure are directed to this and other considerations.